Effects of hydrologic variability and remedial actions on first flush and metal loading from streams draining the Silverton caldera, 1992–2014

Abstract

AbstractThis study examined water quality in the upper Animas River watershed, a mined watershed that gained notoriety following the 2015 Gold King mine release of acid mine drainage to downstream communities. Water‐quality data were used to evaluate trends in metal concentrations and loads over a two‐decade period. Selected sites included three sites on tributary streams and one main‐stem site on the Animas River downstream from the tributary confluences. During the study period, metal concentrations and loads varied seasonally and annually because of hydrologic variability and remedial actions designed to ameliorate the effects of acid mine drainage. Water‐quality data were divided into two periods based on the timing of remedial activities in the watershed. The first period includes active water treatment, surface reclamation and installation of bulkheads in adits; the second period includes the decade following these activities. Water‐quality data were used to estimate annual and monthly zinc loads using the Adjusted Maximum Likelihood Method (using LOADEST software) and U.S. Geological Survey streamflow data. This study presents one of the first applications of LOADEST focused on metal loads. Monthly flow‐weighted concentrations were analysed using a Mann‐Kendall trend test to determine the direction, magnitude, and significance of temporal trends in zinc loading in any given month and using t‐test comparisons between the two periods. Zinc loads estimated for the Animas River below the tributaries indicate decreased zinc loading during the rising limb of the hydrograph in the second period, perhaps reflecting a reduction of snowmelt‐derived zinc load following surface reclamation activities. In contrast, base‐flow zinc loading increased at the main‐stem site, perhaps because of the cessation of water treatment in tributary streams. Flow weighting of monthly load estimates yielded increased statistical significance and enabled more nuanced differentiation between the effects of hydrologic variability and remedial activities on zinc loading.